Comparison
AEO vs GEO
AEO optimizes being quoted directly by answer engines. GEO optimizes being represented well inside generative AI responses. They overlap heavily and are often used together, but both act on retrieval and understanding, not on whether you are recommended and selected once a buyer applies requirements.
What AEO is
Answer Engine Optimization structures content and metadata so answer engines retrieve and quote you, with a citation as the unit of success.
What GEO is
Generative Engine Optimization structures content, entities, and authority so generative AI systems represent your company accurately in the answers they compose.
Where they overlap
Both are retrieval-and-understanding disciplines: clear structure, schema, authoritative sourcing, and consistent entity signals. In practice the tactics overlap so much that many teams treat them as one effort.
Where they differ
AEO is framed around being the quoted answer; GEO is framed around being well-represented in a generated response. The distinction is mostly emphasis. Neither addresses what happens after retrieval, when the buyer adds requirements and the field narrows.
Where both fit in the commercial evaluation lifecycle
AEO and GEO both act at discovery and retrieval, the front of the lifecycle. They help you enter the recommendation set. What decides survival, elimination, and selection happens in the later stages that commercial evaluation studies.